Journal Information
Vol. 1. Issue 1.
Pages 1-40 (April - June 2008)
Share
Share
Download PDF
More article options
Visits
49624
Vol. 1. Issue 1.
Pages 1-40 (April - June 2008)
Original Article
DOI: 10.3921/joptom.2008.36
Open Access
Grading of Iris Color with an Extended Photographic Reference Set
Visits
49624
Luuk Franssen??
Corresponding author
l.franssen@nin.knaw.nl

Corresponding Author: Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands.
, Joris E. Coppens, Thomas J.T.P. van den Berg
Netherlands Institute for Neuroscience, an institute of the Royal, Netherlands Academy of Arts and Sciences. Amsterdam, The Netherlands
This item has received
49624
Visits

Under a Creative Commons license
Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Figures (4)
Show moreShow less
Abstract
Purpose

To present a new iris pigmentation classification system based on comparison of iris pigmentation to a set of 24 standard eye photographs, with the aim of gaining on accuracy and on applicability for retinal straylight studies.

Methods

A reference set of 24 eye photographs was established by ranking the photographs from least (number 1) to most (number 24) iris pigmentation. Reproducibility was tested by grading a sample of 67 eye photographs with this reference set.

Results

The overall variation between observers was 1.46 on a scale of 0 to 25.

Conclusion

The new method is promising to be more accurate than existing iris color classification systems in clinical situations where objective colorimetry-based systems are not available. The method may be useful to assess iris translucency and fundus reflectance as sources of variation in retinal straylight.

Key Words:
iris color
eye pigmentation
grading
straylight
translucency
Resumen
Objetivo

Presentar un nuevo sistema de clasificación de la coloración del iris basado en la comparación de la pigmentación del iris con un conjunto de referencia formado por 24 fotografías de ojos, con el objetivo de lograr una mayor precisión y una mayor aplicabilidad del mismo en los estudios sobre la luz dispersa (parásita) que llega a la retina.

Métodos

Se ha establecido un conjunto de 24 fotografías de ojos, ordenadas de menor (fotografía número 1) a mayor (fotografía número 24) según la cantidad de pigmentación del iris. Para evaluar la reproducibilidad de este sistema, se utilizó una muestra compuesta por 67 fotografías de ojos. Varios observadores asignaron a cada una de las fotografías un valor de la escala de coloración, utilizando para ello el mencionado conjunto de referencia.

Resultados

La variación global entre observadores fue igual a 1,46, en una escala de 0 a 25.

Conclusiones

El nuevo método parece que puede llegar ser más preciso que los actuales sistemas de clasificación de la coloración del iris en aquellas situaciones de la práctica clínica donde no se dispone de sistemas objetivos basados en colorimetría. El método puede resultar útil para evaluar la translucidez del iris y la reflectancia del fondo de ojo como posibles orígenes de la variabilidad que existe entre sujetos de la cantidad de luz dispersa (parásita) que alcanza la retina.

Palabras Clave:
color del iris
pigmentación del ojo
clasificación
luz dispersa
translucidez
Full Text
Introduction

It is known from studies in the past that the amount of pigmentation in the eye wall and fundus influences the quality of the image on the retina of the normal human eye. Two main reasons were identified: part of the light projected on to the retina is not absorbed but is reflected back into the eye by the layers of the fundus,1 and the fact taht the eye wall, including the iris, is not optically opaque.2 Both effects depend on the amount of pigmentation in the fundus and the eye wall respectively. The light originating from fundus reflectance and eye wall translucency does not partake in proper image formation on the retina, but is scattered in the eye to create a veil of light over the retinal image. Together with scattered light originating from optical imperfections in the cornea and the crystalline lens, this light is referred to as retinal straylight. The scatter-induced light veil reduces the contrast of the retinal image and may lead to impairment of the visual function. When this impairment is caused by bright lights at a distance, such as headlights of oncoming cars when driving at night, the term “disability glare” is used.

In previous studies the color of the eye (iris color) was used as an indicator for eye pigmentation. Blue-eyed caucasians were found to have higher retinal straylight values compared to pigmented brown-eyed non-caucasians, leading to the conclusion that pigmentation is a source of variation in straylight in normal eyes.2,3 Van den Berg et al.4 showed that this pigmentation dependence is partly caused by variations in transmission of light through the ocular wall. For dark-brown eyes of pigmented individuals transmission was found to be two orders of magnitude lower than for blue-eyed individuals. Furthermore, the authors speculated that variations in fundus reflectance are also partly responsible for pigmentation dependence of straylight, which was later investigated more thoroughly by Vos and van den Berg.1 The study of van den Berg et al.4 also showed that variation in pigmentation on the blue side of the eye color spectrum has much more influence on the straylight value than variation on the brown side. This can be understood by realizing that the contribution of straylight originating from fundus reflectance and eye wall translucency to the total amount of straylight is larger for less pigmented blue eyes than for well pigmented brown eyes.

To better understand the variation in optical quality of the eye in the normal population, and to be able to more accurately identify sources of increased retinal straylight in pathological eyes, the amount of fundus reflectance and eye wall translucency would need to be estimated, ideally by measuring these two factors directly. However, the techniques to do this are not readily available for most clinicians. Therefore, it would be desirable to have a relatively simple and straightforward way to assess these factors in a clinical environment. Grading of iris color seems to be an obvious candidate.

For iris color to be used as reliable measure of eye pigmentation, its classification should be standardized. In most studies, iris color was subdivided in either 2 (light/dark,5-9 blue/brown,10,11 or light-very light/black-brown12), 3 (blue/grey-green/brown,13,14 blue/mixture of brown, grey, green and/or yellow/brown,15 blue/grey-green-mottled/brown,16 blue/brown/other,17 blue-grey/green-hazel/brown-black,18 or blue/green/brown19), 4 (grey/blue/hazel/brown,20 blue/grey-green/hazel/brown,21 blue/hazel/brown/indeterminate,22 or blue/brown/green/hazel23), 5 (blue/grey/green/hazel/brown24,25 or blue/hazel/green/brown/black26), or 6 (blue/green/hazel/brown/black/not clear27) categories, to be assessed by the investigator and/or the subject. An extensive line of research has been devoted to the effects of prostaglandin analogs and prostamides on iris pigmentation.28,29 These are drugs used as ocular hypotensive agents in glaucoma patients. Most of these studies used 8, 9 or 10 iris color categories, based on a method introduced by Alm and Stjernschantz.30

These classification systems, which can be characterized by the term “color naming”, are very subjective, since they do not involve comparison of the eye color to some kind of standardized reference. To improve on this situation, iris color classification systems based on a comparison with some kind of color standard, such as a color chart with 331 or 1127 colors, 15 painted glass anterior eye segments,32 3 pictures of artificial eyes,33 or the 5-grade Boys-Smith pigment gradation lens,34 have been used. Also, sets of standardized photographs of real eyes have been used as a reference. Moss et al.35 used a reference set of 6 red reflex photographs, obtained with dilated pupils. In the Beaver Dam Eye Study, a set of 3 reference photographs was defined,36 to be practically used to classify eye color in 337 or 438 categories. A modified version was used to define 5 categories.39 Seddon et al.40 developed a system with 4 reference photographs (5 categories), that was also used in later studies.41-43

Most of these grading systems use 2 to 5 categories for eye color, which is too coarse (discretisation error too high) to discern the subtle differences on the blue side which are expected to induce relatively strong variations in retinal straylight, as explained above. In the last decade some objective classification systems have been proposed, based on automated image analysis by a computer using a calibrated software package (Bee WH, et al. IOVS 1997;38:ARVO Abstract 3797).44-48 Delori et al. (Delori FC, et al. IOVS 1991;32:ARVO Abstract 2333) explored the use of iris reflectometry as a potential tool for the evaluation of iris pigmentation. These methods offer objective and accurate ways to measure iris color. However, they are not readily available for most clinicians.

In this article, we present a new system for the classification of iris pigmentation, based on the comparison of iris pigmentation to a set of 24 standard photographs. It is intended to be a quick and easy-to-use system that is more accurate than the existing systems. A similar system for the evaluation of diffuse atrophy of the retinal nerve fiber layer was proposed earlier.49 To be precise, color is a bit of a misnomer for iris classification, because color is essentially a two-dimensional system, while the iris is rarely homogeneous in color. Therefore, we chose to develop a classification system based on (subjective) estimation of iris pigmentation, intended to give a one-dimensional quantity.

Methods

The eyes of 32 volunteers were photographed with a Sony DSC-S75 digital camera under standardized illumination conditions and camera settings (eyes illuminated by a ring-shaped light derived by fiber optics from a halogen lamp, no flash, shutter speed 1/60 s, ISO value 200, fixed white balance). The volunteers were recruited from coworkers and students within the institute. Care was taken that the whole spectrum of possible iris colors would be included. For the reference set, 24 out of 32 photographs were selected by one observer based on image quality and variation in iris color. Three of these 24 eyes were non-Caucasian. Institutional Review Board (IRB)/Ethics Committee decided that approval was not required for this study.

The 24 photographs were independently ranked from least (number 1) to most (number 24) average iris pigmentation by 4 observers with no color deficiencies. The final order for the reference set was determined by the mean scores of these 4 observers.

To investigate the reproducibility of this classification system, a test sample of 67 eye photographs (different from the ones used for the reference set) was graded according to the reference set by 4 observers with no color deficiencies, using a scale from 0 (zero discernable pigmentation) to 25 (darker than picture 24). The observers, of which two had also ranked the reference set, were asked to grade each test photograph on the scale created by the reference set in a global manner, as opposed to comparing each test photograph to each picture of the reference set in detail. The photographs in the test sample had a lower image quality and were taken under different illumination conditions than those in the reference set (compact digital camera with flash).

Results

Figure 1 shows the individual ranking scores of the 24 reference photographs as a function of the mean score for each photograph. The deviations from the mean are given in figure 2. The overall standard deviation is 1.22. The figures show a higher spread of data points on the low side (bluish iris colors). The reference set of 24 photographs is presented in figure 3, ordered according to the average ranking of the 4 observers.

Figure 1.

Ranking of 24 eye photographs by 4 observers on the basis of iris pigmentation (least=1, most=24). Individual scores are plotted as a function of the mean score. More spread around the x=y line means less agreement between the observers.

(0.06MB).
Figure 2.

Similar to figure 1, only now the deviation from the mean is plotted against the mean score. The dashed lines represent the overall 95% confidence interval, based on an overall standard deviation of 1.22.

(0.07MB).
Figure 3.

Reference set for classification of iris pigmentation, in order from least (number 1) to most (number 24) iris pigmentation. The presented order is based on ranking by 4 observers. For practical use, this figure can be obtained from the authors upon request.

(0.61MB).

The deviations from the mean scores for the test sample of 67 photographs are plotted as a function of the mean score in figure 4. The overall standard deviation is 1.46. Part of this standard deviation is caused by small but statistically significant systematic differences between the 4 observers (average deviations 0.49, -0.68, 0.49, -0.31, respectively, corresponding to a standard deviation of these average deviations of 0.59). Linear trend lines are plotted for each observer.

Figure 4.

Reproducibility of the iris classification procedure. The iris pigmentation in 67 eye photographs was evaluated by 4 observers using the reference photographs presented in figure 3. The deviation from the mean score is plotted against the mean score. The dashed lines represent the overall 95% confidence interval, based on an overall standard deviation of 1.46. To investigate systematic differences between observers, trend lines for the individual data sets are also plotted.

(0.13MB).
Discussion

In this article, we presented a new classification system for iris pigmentation, using a set of 24 standard photographs as a reference. This system assesses iris pigmentation in a more quantitative way than the systems that have been used in the literature. Therefore, the new system might prove to be useful to gain more detailed knowledge about iris pigmentation, which is a source of variation for retinal straylight.

To establish the reference set of 24 photographs, some arbitrary choices had to be made. Since the photographs were chosen from a rather limited population sample, it is unclear to what extent the sample represents the whole population. Some areas in the range of iris pigmentations may be underor overrepresented in the chosen reference set. Furthermore, one might wonder whether the order would depend on the observers participating in the study. However, we are confident that these would be marginal effects.

We are strengthened in this assumption because a remarkable agreement between observers was found, in both the establishment of the order in the reference set (Figure 1and2), and the reproducibility test (Figure 4). The larger variation in data points on the low side (bluish iris colors) in figure 1 and 2 might suggest that it is more difficult to grade bluish than brownish iris colors. However, another explanation might be that in this reference set the differentiation of blue colors is more detailed than the differentiation on the brown side, giving rise to more noise on the blue side. In fact, this noise could be used to define a new reference set that has an equal accuracy over the whole scale, which would be desirable for general use of the system. For straylight applications, a more detailed reference set on the blue side might be useful, as explained in the introduction.

The overall standard deviation of 1.46 justifies the use of the relatively high amount of (24) categories for iris pigmentation. The (small) systematic difference in behavior between observers 1 and 3 on the one side and observer 2 on the other side might be caused by a different way of appreciation of the differences in image quality and general color appearance between the test sample and the reference set. The positive slope of observer 4 in figure 4 might indicate that this observer is more likely to use the extreme ends of the scale than the other observers.

The incentive for this study was the need for a relatively simple method to assess iris translucency and fundus reflectance as sources of variation in retinal straylight. Such a method was established by defining a reference set of eye photographs with different grades of iris pigmentation, containing more detail for the bluish colors than existing iris color grading systems. The scoring error of about 1.5 on a scale from 0 to 25 suggests a higher discriminative power than that of the existing systems, which have a higher discretisation error than this scoring error. However, we did not actually compare our method to the existing systems. We believe that our method can be an improvement over existing iris color classification systems in clinical situations where objective colorimetry-based systems are not available.

References
[1.]
J.J. Vos, T.J.T.P. van den Berg.
On the course of the disability glare function and its attribution to components of ocular scatter.
CIE collection, 124 (1997), pp. 11-29
[2.]
J.K. IJspeert, P.W. de Waard, T.J.T.P. van den Berg, P.T. de Jong.
The intraocular straylight function in 129 healthy volunteers; dependence on angle, age and pigmentation.
Vision Res., 30 (1990), pp. 699-707
[3.]
D.B. Elliott, S. Mitchell, D. Whitaker.
Factors affecting light scatter in contact lens wearers.
Optom Vis Sci., 68 (1991), pp. 629-633
[4.]
T.J.T.P. van den Berg, J.K. IJspeert, P.W. de Waard.
Dependence of intraocular straylight on pigmentation and light transmission through the ocular wall.
Vision Res., 31 (1991), pp. 1361-1367
[5.]
J.R. Dillon, C.W. Tyhurst, R.L. Yolton.
The mydriatic effect of tropicamide on light and dark irides.
J Am Optom Assoc., 48 (1977), pp. 653-658
[6.]
J.J. Weiter, F.C. Delori, G.L. Wing, K.A. Fitch.
Relationship of senile macular degeneration to ocular pigmentation.
Am J Ophthalmol., 99 (1985), pp. 185-187
[7.]
M.A. Sandberg, A.R. Gaudio, S. Miller, A. Weiner.
Iris pigmentation and extent of disease in patients with neovascular age-related macular degeneration.
Invest Ophthalmol Vis Sci., 35 (1994), pp. 2734-2740
[8.]
J.W. Harbour, M.A. Brantley Jr., H. Hollingsworth, M. Gordon.
Association between posterior uveal melanoma and iris freckles, iris naevi, and choroidal naevi.
Br J Ophthalmol., 88 (2004), pp. 36-38
[9.]
J.W. Harbour, M.A. Brantley Jr., H. Hollingsworth, M. Gordon.
Association between choroidal pigmentation and posterior uveal melanoma in a white population.
Br J Ophthalmol., 88 (2004), pp. 39-43
[10.]
J.V. Lovasik, H. Kergoat.
Time course of cycloplegia induced by a new phenylephrine-tropicamide combination drug.
Optom Vis Sci., 67 (1990), pp. 352-358
[11.]
S. Patel, S. Laidlaw, L. Mathewson, et al.
Iris colour and the influence of local anaesthetics on pre-corneal tear film stability.
Acta Ophthalmol (Copenh), 69 (1991), pp. 387-392
[12.]
M.C. Leske, S.Y. Wu, B. Nemesure, A. Hennis.
Risk factors for incident nuclear opacities.
Ophthalmology, 109 (2002), pp. 1303-1308
[13.]
V. Krizek.
Iris colour and composition of urinary stones.
Lancet, 1 (1968), pp. 1432
[14.]
M.A. Tucker, J.A. Shields, P. Hartge, et al.
Sunlight exposure as risk factor for intraocular malignant melanoma.
N Engl J Med., 313 (1985), pp. 789-792
[15.]
L.G. Hyman, A.M. Lilienfeld, F.L. Ferris III, S.L. Fine.
Senile macular degeneration: a case-control study.
Am J Epidemiol., 118 (1983), pp. 213-227
[16.]
T. Vinding.
Pigmentation of the eye and hair in relation to age-related macular degeneration. An epidemiological study of 1000 aged individuals.
Acta Ophthalmol (Copenh), 68 (1990), pp. 53-58
[17.]
M.L. Barrenas, F. Lindgren.
The influence of eye colour on susceptibility to TTS in humans.
Br J Audiol., 25 (1991), pp. 303-307
[18.]
B.R. Hammond Jr., K. Fuld, D.M. Snodderly.
Iris color and macular pigment optical density.
Exp Eye Res., 62 (1996), pp. 293-297
[19.]
M.C. Acosta, M.L. Alfaro, F. Borras, et al.
Influence of age, gender and iris color on mechanical and chemical sensitivity of the cornea and conjunctiva.
Exp Eye Res., 83 (2006), pp. 932-938
[20.]
M.F. Carlin, R.L. McCroskey.
Is eye color a predictor of noise-induced hearing loss?.
Ear Hear, 1 (1980), pp. 191-196
[21.]
R.M. Barr-Hamilton, L.M. Matheson, D.G. Keay.
Ototoxicity of cis-platinum and its relationship to eye colour.
J Laryngol Otol., 105 (1991), pp. 7-11
[22.]
R.N. Frank, J.E. Puklin, C. Stock, L.A. Canter.
Race, iris color, and age-related macular degeneration.
Trans Am Ophthalmol Soc., 98 (2000), pp. 109-115
[23.]
C.J. Hammond, H. Snieder, T.D. Spector, C.E. Gilbert.
Factors affecting pupil size after dilatation: the Twin Eye Study.
Br J Ophthalmol., 84 (2000), pp. 1173-1176
[24.]
J. Rootman, R.P. Gallagher.
Color as a risk factor in iris melanoma.
Am J Ophthalmol., 98 (1984), pp. 558-561
[25.]
F.G. Holz, B. Piguet, D.C. Minassian, et al.
Decreasing stromal iris pigmentation as a risk factor for age-related macular degeneration.
Am J Ophthalmol., 117 (1994), pp. 19-23
[26.]
N.W. Todd, C.S. Alvarado, D.B. Brewer.
Cisplatin in children: hearing loss correlates with iris and skin pigmentation.
J Laryngol Otol., 109 (1995), pp. 926-929
[27.]
T. Frudakis, M. Thomas, Z. Gaskin, et al.
Sequences associated with human iris pigmentation.
Genetics, 165 (2003), pp. 2071-2083
[28.]
J.W. Stjernschantz, D.M. Albert, D.N. Hu, et al.
Mechanism and clinical significance of prostaglandin-induced iris pigmentation.
Surv Ophthalmol., 47 (2002), pp. S162-S175
[29.]
B.E. McCarey, B.M. Kapik, F.E. Kane.
Low incidence of iris pigmentation and eyelash changes in 2 randomized clinical trials with unoprostone isopropyl 0.15%.
Ophthalmology, 111 (2004), pp. 1480-1488
[30.]
A. Alm, J. Stjernschantz.
Effects on intraocular pressure and side effects of 0.005% latanoprost applied once daily, evening or morning. A comparison with timolol. Scandinavian Latanoprost Study Group.
Ophthalmology, 102 (1995), pp. 1743-1752
[31.]
L. Semes, A. Shaikh, G. McGwin, J.D. Bartlett.
The relationship among race, iris color, central corneal thickness, and intraocular pressure.
Optom Vis Sci., 83 (2006), pp. 512-515
[32.]
L.Z. Bito, A. Matheny, K.J. Cruickshanks, et al.
Eye color changes past early childhood. The Louisville Twin Study.
Arch Ophthalmol., 115 (1997), pp. 659-663
[33.]
W. Uter, A. Pfahlberg, B. Kalina, et al.
Inter-relation between variables determining constitutional UV sensitivity in Caucasian children.
Photodermatol Photoimmunol Photomed, 20 (2004), pp. 9-13
[34.]
S.Y. Chou, C.K. Chou, T.M. Kuang, W.M. Hsu.
Incidence and severity of iris pigmentation on latanoprost-treated glaucoma eyes.
[35.]
S.E. Moss, R. Klein, M.B. Meuer, B.E. Klein.
The association of iris color with eye disease in diabetes.
Ophthalmology, 94 (1987), pp. 1226-1231
[36.]
R. Klein, B.E.K. Klein.
Beaver Dam Eye Study: Manual of Operations.
University of Wisconsin-Madison, (1991),
[37.]
R. Klein, B.E. Klein, S.C. Jensen, K.J. Cruickshanks.
The relationship of ocular factors to the incidence and progression of age-related maculopathy.
Arch Ophthalmol., 116 (1998), pp. 506-513
[38.]
P. Mitchell, W. Smith, J.J. Wang.
Iris color, skin sun sensitivity, and agerelated maculopathy. The Blue Mountains Eye Study.
Ophthalmology, 105 (1998), pp. 1359-1363
[39.]
H. Hashemi, A.H. Kashi, A. Fotouhi, K. Mohammad.
Distribution of intraocular pressure in healthy Iranian individuals: the Tehran Eye Study.
Br J Ophthalmol., 89 (2005), pp. 652-657
[40.]
J.M. Seddon, C.R. Sahagian, R.J. Glynn, et al.
Evaluation of an iris color classification system. The Eye Disorders Case-Control Study Group.
Invest Ophthalmol Vis Sci., 31 (1990), pp. 1592-1598
[41.]
J.D. Twelker, D.O. Mutti.
Retinoscopy in infants using a near noncycloplegic technique, cycloplegia with tropicamide 1%, and cycloplegia with cyclopentolate 1%.
Optom Vis Sci., 78 (2001), pp. 215-222
[42.]
W.M. Broekmans, A.A. Vink, E. Boelsma, et al.
Determinants of skin sensitivity to solar irradiation.
Eur J Clin Nutr., 57 (2003), pp. 1222-1229
[43.]
J.C. Khan, H. Shahid, D.A. Thurlby, et al.
Age related macular degeneration and sun exposure, iris colour, and skin sensitivity to sunlight.
Br J Ophthalmol., 90 (2006), pp. 29-32
[44.]
E.J. German, M.A. Hurst, D. Wood, J. Gilchrist.
A novel system for the objective classification of iris colour and its correlation with response to 1% tropicamide.
Ophthalmic Physiol Opt., 18 (1998), pp. 103-110
[45.]
M. Melgosa, M.J. Rivas, L. Gomez, E. Hita.
Towards a colorimetric characterization of the human iris.
Ophthalmic Physiol Opt., 20 (2000), pp. 252-260
[46.]
T. Takamoto, B. Schwartz, L.B. Cantor, et al.
Measurement of iris color using computerized image analysis.
Curr Eye Res., 22 (2001), pp. 412-419
[47.]
B. Niggemann, G. Weinbauer, F. Vogel, R. Korte.
A standardized approach for iris color determination.
Int J Toxicol., 22 (2003), pp. 49-51
[48.]
Fan S, Dyer CR, Hubbard L. Quantification and correction of iris color. Technical Report 1495. 2003. Department of Computer Sciences, University of Wisconsin-Madison.
[49.]
A.G.J.E. Niessen, T.J.T.P. van den Berg, C.T. Langerhorst, P.M.M. Bossuyt.
Grading of retinal nerve fiber layer with a photographic reference set.
Am J Ophthalmol., 120 (1995), pp. 577-586
Copyright © 2008. Spanish Council of Optometry
Journal of Optometry

Subscribe to our newsletter

Article options
Tools

Are you a health professional able to prescribe or dispense drugs?

Cookies policy
To improve our services and products, we use cookies (own or third parties authorized) to show advertising related to client preferences through the analyses of navigation customer behavior. Continuing navigation will be considered as acceptance of this use. You can change the settings or obtain more information by clicking here.